Summary  
This chapter covers how to customize axis ticks and labels in plots: setting tick positions and custom text with xticks() and yticks(), styling them (rotation, font size, etc.), and adding styled axis labels with xlabel() and ylabel().  

General domain of usage  
Data visualization

## Ticks Customization

To customize **ticks**, use:

* `xticks` for the x-axis,
* `yticks` for the y-axis.

Both accept:

* `ticks` — positions of ticks (empty list removes ticks);
* `labels` — custom text for those positions.

Additional keyword arguments let you style tick labels (e.g., rotation, font size).

Below is a plot using these tools:

Everything seems to be pretty fine with this plot, however, it would be better to have more years on the x-axis in this range (1995-2020). Let's use `xticks()` for this purpose:

import pandas as pd
import matplotlib.pyplot as plt

url = 'https://staging-content-media-cdn.codefinity.com/courses/47339f29-4722-4e72-a0d4-6112c70ff738/weather_data.csv'
weather_df = pd.read_csv(url, index_col=0)

plt.plot(weather_df['Boston'], label='Boston')
plt.plot(weather_df['Seattle'], label='Seattle')

plt.title('Boston and Seattle average yearly temperatures')
plt.legend(loc='upper left')

plt.xticks(range(1995, 2021, 2), rotation=30)

plt.show()

Every second year is displayed on the x-axis thanks to `range(1995, 2021, 2)`.
Labels are rotated 30° for readability.
Tick labels can also be manually set by passing a list to `labels`.

## Axes Labels Customization

Use `xlabel()` and `ylabel()` to set axis labels. Each takes a single string.

import pandas as pd
import matplotlib.pyplot as plt

url = 'https://content-media-cdn.codefinity.com/courses/47339f29-4722-4e72-a0d4-6112c70ff738/weather_data.csv'
weather_df = pd.read_csv(url, index_col=0)

plt.plot(weather_df['Boston'], label='Boston')
plt.plot(weather_df['Seattle'], label='Seattle')

plt.title('Boston and Seattle average yearly temperatures')
plt.legend(loc='upper left')
plt.xticks(range(1995, 2021, 2), rotation=30)
plt.ylabel('Temperature, °F')

plt.show()

You can style labels with options such as `fontsize` and `color`.
The `loc` argument controls label placement:

* For x-labels: `'left'`, `'center'`, `'right'`;
* For y-labels: `'top'`, `'center'`, `'bottom'`.

You can explore more in the documentation: <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.xlabel.html" target="_blank"><svg width="1em" height="1em" viewBox="0 0 30 32" fill="none" xmlns="http://www.w3.org/2000/svg"><path fill="none" stroke="#098f67" style="stroke: var(--color1, #098f67)" stroke-linejoin="miter" stroke-linecap="round" stroke-miterlimit="4" stroke-width="2.4156" d="M17.289 17.305v0c-1.754 1.754-4.597 1.754-6.351 0l-7.76-7.759c-1.755-1.755-1.755-4.601 0-6.356v0c1.753-1.753 4.595-1.756 6.351-0.005l6.208 6.187"></path><path fill="none" stroke="#098f67" style="stroke: var(--color1, #098f67)" stroke-linejoin="miter" stroke-linecap="round" stroke-miterlimit="4" stroke-width="2.4156" d="M12.504 13.97v0c1.754-1.754 4.597-1.754 6.351 0l7.762 7.762c1.754 1.754 1.754 4.597 0 6.351v0c-1.754 1.754-4.597 1.754-6.351 0l-5.953-5.953"></path></svg> <code>xlabel()</code></a> and <a href="https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.ylabel.html#matplotlib.pyplot.ylabel" target="_blank"><svg width="1em" height="1em" viewBox="0 0 30 32" fill="none" xmlns="http://www.w3.org/2000/svg"><path fill="none" stroke="#098f67" style="stroke: var(--color1, #098f67)" stroke-linejoin="miter" stroke-linecap="round" stroke-miterlimit="4" stroke-width="2.4156" d="M17.289 17.305v0c-1.754 1.754-4.597 1.754-6.351 0l-7.76-7.759c-1.755-1.755-1.755-4.601 0-6.356v0c1.753-1.753 4.595-1.756 6.351-0.005l6.208 6.187"></path><path fill="none" stroke="#098f67" style="stroke: var(--color1, #098f67)" stroke-linejoin="miter" stroke-linecap="round" stroke-miterlimit="4" stroke-width="2.4156" d="M12.504 13.97v0c1.754-1.754 4.597-1.754 6.351 0l7.762 7.762c1.754 1.754 1.754 4.597 0 6.351v0c-1.754 1.754-4.597 1.754-6.351 0l-5.953-5.953"></path></svg> <code>ylabel()</code></a>.


Study More

import unittest
import ast
import inspect
import user_code  # This should be your solution file/module name


def _dynamic_test(test_case, condition, success_message, failure_message):
    if condition:
        test_case._testMethodName = success_message
        test_case.assertTrue(True, success_message)
    else:
        test_case._testMethodName = failure_message
        test_case.fail(failure_message)


class TestPlotCustomization(unittest.TestCase):

    @classmethod
    def setUpClass(cls):
        source = inspect.getsource(user_code)
        cls.tree = ast.parse(source)

        # Gather all function calls
        cls.calls = [
            node for node in ast.walk(cls.tree)
            if isinstance(node, ast.Call) and isinstance(node.func, ast.Attribute)
        ]

    def test_xticks_data_linear_used(self):
        xticks_call = next((call for call in self.calls if call.func.attr == 'xticks'), None)
        arg_id = xticks_call.args[0].id if xticks_call and isinstance(xticks_call.args[0], ast.Name) else None
        _dynamic_test(
            self,
            arg_id == 'data_linear',
            "Used `data_linear` as x-axis ticks",
            f"Expected `data_linear` as x-axis ticks, got `plt.xticks({arg_id})`"
        )

    def test_xlabel_correct_label_and_loc(self):
        xlabel_call = next((call for call in self.calls if call.func.attr == 'xlabel'), None)
        label = xlabel_call.args[0].s if xlabel_call and isinstance(xlabel_call.args[0], ast.Str) else None
        loc_kwarg = next((kw.value.s for kw in xlabel_call.keywords if kw.arg == 'loc'), None) if xlabel_call else None
        _dynamic_test(
            self,
            label == 'x' and loc_kwarg == 'right',
            "Correct x-axis label and location set: xlabel('x', loc='right')",
            f"Incorrect x-axis label or location: label={label}, loc={loc_kwarg}"
        )

    def test_ylabel_correct_label_loc_and_rotation(self):
        ylabel_call = next((call for call in self.calls if call.func.attr == 'ylabel'), None)
        label = ylabel_call.args[0].s if ylabel_call and isinstance(ylabel_call.args[0], ast.Str) else None
        loc_kwarg = next((kw.value.s for kw in ylabel_call.keywords if kw.arg == 'loc'), None) if ylabel_call else None
        rotation_kwarg = next((kw.value.n for kw in ylabel_call.keywords if kw.arg == 'rotation'), None) if ylabel_call else None
        _dynamic_test(
            self,
            label == 'y' and loc_kwarg == 'top' and rotation_kwarg == 0,
            "Correct y-axis label with location and rotation: ylabel('y', loc='top', rotation=0)",
            f"Incorrect y-axis label, loc, or rotation: label={label}, loc={loc_kwarg}, rotation={rotation_kwarg}"
        )


if __name__ == '__main__':
    unittest.main()


test_axes.py

Learn how to explore and communicate data through visual analysis. The course covers creating common plots, customizing visualizations, and using statistical charts to examine data distributions, relationships, and patterns. Exploratory data analysis techniques are applied to identify trends, anomalies, and insights in real-world datasets.

Axes

Ticks Customization

Axes Labels Customization

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